Forced oscillation technique for early detection of the effects of smoking and COPD: contribution of fractional-order modeling

Abstract

Purpose

The aim of the present study was to evaluate the performance of the forced oscillation technique (FOT) for the early diagnosis of the effects of smoking and COPD. The contributions of the integer-order (InOr) and fractional-order (FrOr) models were also evaluated.

Patients and methods

In total, 120 subjects were analyzed: 40 controls, 40 smokers (20.3±9.3 pack-years) and 40 patients with mild COPD.

Results

Initially, it was observed that traditional FOT parameters and the InOr and FrOr models provided a consistent description of the COPD pathophysiology. Mild COPD introduced significant increases in the FrOr inertance, damping factor and hysteresivity (P<0.0001). These parameters were significantly correlated with the spirometric parameters of central and small airway obstruction (P<0.0001). The diagnostic accuracy analyses indicated that FOT parameters and InOr modeling may adequately identify these changes (area under the receiver operating characteristic curve – AUC >0.8). The use of FrOr modeling significantly improved this process (P<0.05), allowing the early diagnosis of smokers and patients with mild COPD with high accuracy (AUC >0.9).

Conclusion

FrOr modeling improves our knowledge of modifications that occur in the early stages of COPD. Additionally, the findings of the present study provide evidence that these models may play an important role in the early diagnosis of COPD, which is crucial for improving the clinical management of the disease.

Keywords:

• COPD
• oscillation mechanics
• smoking
• respiratory modeling
• integer-order modeling
• respiratory impedance

Supplementary material

Supplementary data S1

Instrumentation

FOT measurements were performed using an instrument developed in our laboratory and were characterized by low pressure oscillations in the frequency range between 4 and 32 Hz with an amplitude of 1 cm H₂O.¹ This signal was produced by a speaker and transmitted to the respiratory system by a mouthpiece. The resulting flow and pressure signals were measured near the mouth by a pneumotachometer and a pressure transducer, respectively. After amplification, these signals were processed using the Fourier transform (F) to estimate the respiratory impedance (Zrs) by the ratio between the pressure (P) and respiratory flow (V´) signals [Zrs=F(P)/F(V´)]. During the FOT tests, three trials of approximately 16 seconds were performed with the individuals sitting with their trunk and their head in the neutral position and using a nasal clip. The subjects breathed quietly through a silicone mouthpiece and held their cheeks with their hands.

Reference

• de MeloPLWerneckMMGiannella-NetoANew impedance spectrometer for scientific and clinical studies of the respiratory systemReview of Scientific Instruments200071728672872
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Acknowledgments

The Brazilian Council for Scientific and Technological Development (CNPq) and Rio de Janeiro State Research Supporting Foundation (FAPERJ) supported this study. This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code 001.

Disclosure

The authors report no conflicts of interest in this work.